AI can do heavy lifting in payroll, freeing up more time for professionals to be strategic

June 12, 2025

Todd Humber

Organizations that have invested in payroll automation “save an average of two working days per week, totaling about 96 days per year,” according to Cristina Goldt, general manager of workforce and pay at Workday.

The potential for this dramatic efficiency improvement is transforming how companies process compensation while raising important questions about maintaining the human touch when handling employee pay.

“AI is being used in payroll to automate tasks like calculating taxes, data entry, conducting audits, managing expenses, and tracking time,” she says.

HCM Podcast

Produced with Google Notebook LM Using AI Narration

These efficiency gains allow payroll departments to pivot and focus more on strategic activities.

“This increased efficiency enables them to shift their focus to higher-level strategic work and areas where human expertise is crucial for driving business outcomes,” she adds, which is something leaders clearly want.

“While 92 per cent of senior decision-makers recognize the strategic impact of payroll, 89 per cent believe their current payroll solution could offer more strategic insights. This indicates a significant opportunity for payroll professionals to leverage their data for things like executive decision-making, enhancing the employee experience, and better serving the business.”

The trust and transparency challenge

Julie Develin, senior partner for human insights at UKG, says organizations using AI for payroll and compensation decisions must be transparent with employees about how these systems work.

“Organizations that don’t tell their employees how they’re utilizing AI to make decisions have a problem with trust. “There is a disconnect between how employers are utilizing AI to make decisions — payroll and otherwise — versus what employees know about how they’re using AI to make decisions.”

This transparency gap can undermine employee confidence in compensation decisions, particularly when AI systems flag potential issues or recommend adjustments.

“Why am I to trust you if you tell me, ‘Oh yeah, AI says you’re being paid fairly?’ Who’s AI?” Develin says. “AI doesn’t think. AI doesn’t talk. You can’t see AI’s affect. It’s just black and white. And when we deal in the black and white, we get away from the fact that an employee is not going to remember what you say. They’re going to remember how you made them feel.”

When employees question their compensation or believe they’re underpaid, simply referring to an AI system’s recommendation isn’t sufficient. Human judgment and empathetic communication remain essential.

“Payroll professionals, especially if they’re utilizing AI tools and they’re making decisions based on what AI is telling them, have to be prepared to have hard conversations with employees,” Develin adds. “And they need to know the answers to the questions before the questions are asked.”

” Organizations that have invested in payroll automation “save an average of two working days per week, totaling about 96 days per year,” according to Cristina Goldt, general manager of workforce and pay at Workday. ”

A holistic approach to compensation

Lisa Haydon, founder and CEO of Halifax-based Pivotal Growth, says compensation decisions should never be viewed in isolation but rather as part of a broader performance management framework.

“Compensation and pay increases are based on performance. If it’s not holistically done and integrated, then the payroll and compensation is inaccurate.”

She also points to the importance of creating an environment where employees feel comfortable discussing compensation concerns.

“One of the hardest things to do is to raise concerns when you don’t agree with your salary or pay increase,” said says. “If the work climate doesn’t have a connected psychological safety to ask, challenge and push — then there’s a possibility that if there’s an imperfection in it, you’ve got a workforce that becomes even more disengaged.”

Managing irregularities and ensuring accuracy

One of AI’s strengths in payroll processing is its ability to identify patterns and flag potential irregularities. However, this capability must be paired with robust human review processes, says Goldt.

“When AI flags payroll or financial irregularities, a streamlined human review process is key. Flagged items should be directed to human expert reviewers with sufficient contextual data from the AI. These reviewers can then analyze the information to distinguish between false positives and genuine problems, identifying root causes and determining necessary actions.”

The learning should flow both ways, creating a continuous improvement cycle, she adds.

“Importantly, what the human team learns should help the AI get better at spotting things correctly in the future. Keeping good records of all this helps keep things on track and helps us make the whole system even smarter over time.”

Develin notes organizations should implement clear workflows and conduct regular audits to ensure AI systems are functioning as intended without introducing errors.

“Ensuring that the right eyes are on the information and then periodically auditing what your AI tools are putting out there to ensure fairness and balance and that everything’s working properly [is critical],” Develin says. “Because the last thing you want to do is have to go back and take money away from employees — people don’t like when you mess with their money.”

Employers also need to review their entire payroll process before implementing AI solutions.

“I think it’s important for organizations to review all of their processes and also the software that they’re utilizing and who’s utilizing what software,” Develin adds. “This has to be intentional. There has to be intentionality behind this.”

Preventing fraud and misuse

As AI tools become more sophisticated, so too do the potential avenues for misuse. Recent media reports have highlighted how AI image generation can be used to create fake receipts for expense reports, for example — raising concerns about new forms of fraud.

“We don’t talk a lot about how AI is used by bad actors,” Develin says. “I [have] a lot of discussions about employee relations and AI and how employees can utilize AI tools to do nefarious things.”

She says having clear frameworks and policies in place becomes crucial when confronting these challenges.

“When that does happen, then you have things in place where you can make decisions. And that decision is pretty easy, right?”

Develin adds AI tools don’t turn ethical employees into fraudsters. “It’s like plagiarism. I’m a professor, and I tell my students, ‘Listen, you’re going to get out of this class what you put into it. There are AI tools that can help you write your papers, but if you rely on that, you’re not going to learn anything.’ So as people, it’s also taking individual responsibility.”

Goldt adds that as AI technologies continue to evolve, the future of payroll processing appears to be one where AI and humans work in complementary roles.

“It’s about AI and people working together to drive efficiency while ensuring accuracy.”

This collaborative approach — where AI systems handle routine processing while enabling payroll professionals to focus on more strategic activities — offers the most promising path forward for organizations seeking to modernize their payroll functions while maintaining the human touch that employees expect when it comes to their compensation.

What are your thoughts on